code: def __init__(
      self, num_bins=100, pos_per_bin=10, neg_per_bin=10, **kwargs
  ):
      super().__init__(**kwargs)
      self.num_bins = num_bins
      self.pos_per_bin = pos_per_bin
      self.neg_per_bin = neg_per_bin
      self.add_to_recordable_attributes(
          list_of_names=["pos_per_bin", "neg_per_bin"], is_stat=False
      )
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/miners/uniform_histogram_miner.py
imports: import torch
  from ..utils import loss_and_miner_utils
  from .base_miner import BaseMiner
label_desc: Use image node_id 1 to create a new UniformHistogramMiner object from inherited base classes: BaseMiner with example: obj = UniformHistogramMiner(num_bins, pos_per_bin, neg_per_bin)